Incremental and accuracy-aware personalized pagerank through scheduled approximation

• Main Authors: ZHU, Fanwei, FANG, Yuan, CHANG, Kevin Chen-Chuan, YING, Jing
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2013
• Subjects: Approximation errors; Computation algorithm; Constant time; Efficient computation; Graph sizes; Personalized PageRank; Random Walk; Real-world graphs; Databases and Information Systems; Numerical Analysis and Scientific Computing
• Online Access: https://ink.library.smu.edu.sg/sis_research/4071; https://ink.library.smu.edu.sg/context/sis_research/article/5074/viewcontent/p481_zhu.pdf
• Institution: Singapore Management University

As Personalized PageRank has been widely leveraged for ranking on a graph, the efficient computation of Personalized PageRank Vector (PPV) becomes a prominent issue. In this paper, we propose FastPPV, an approximate PPV computation algorithm that is incremental and accuracy-aware. Our approach hinge...